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GRACE water-storage deficits and surpluses decayed at the same rate on 2,243 land cells in 2002-2026; both stayed longer after extremes than linear precipitation models predict

Question: do terrestrial water-storage deficits decay more slowly than surpluses after the precipitation response is removed? Approach: we averaged CSR GRACE/GRACE-FO RL06.3 mascons (2002-04 to 2026-06) and GPCP v2.3 precipitation to 2,243 ice-free land cells of 2.5 degrees. We removed a monthly climatology and a linear trend. On each cell we fit a precipitation-forced storage model with separate decay coefficients for deficits (a-) and surpluses (a+). We compared the results with 1,000 simulations of a symmetric linear model that use the observed precipitation and block-resampled residuals. Results: the global median a- minus a+ was 0.005 (null 95% range -0.025 to 0.012, p = 0.22). A noise-robust instrumental estimate, a kink at the cell median, a state-dependent precipitation gain and half-recovery times also gave no difference from the null. The test detected an injected asymmetry of 0.05 in all 100 simulations. On 2015-2026 data, the asymmetric model did not forecast better than the symmetric model (median error change 0.0%). After peaks larger than 1 standard deviation, both deficits and surpluses kept 0.08-0.09 of the peak more than a one-reservoir model predicts at 5-12 months (p = 0.001 each), with no sign difference. A two-time-scale model reduced this excess to 0.04-0.05 and decreased out-of-sample error in 77% of cells. Conclusion: at these scales, storage recovery is sign-symmetric but has more than one time scale. Limitations: 2.5 degree monthly scale, precipitation as the only forcing, short records, a trend-adjusted baseline, and simple glacier masks.

GRACE · terrestrial water storage · drought recovery · persistence asymmetry · GPCP · linear reservoir · hydrological memory · null model · threshold autoregression

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References

11
  1. usesdoi:10.1002/2016JB013007

    CSR GRACE mascon method (Save, Bettadpur and Tapley 2016); we use the CSR RL06.3 mascon product and land mask.

  2. useshttps://download.csr.utexas.edu/outgoing/grace/RL0603_mascons/

    Source of the GRACE/GRACE-FO RL06.3 mascon file and land mask.

  3. usesdoi:10.3390/atmos9040138

    GPCP v2.3 monthly precipitation (Adler et al. 2018), the model forcing.

  4. useshttps://downloads.psl.noaa.gov/Datasets/gpcp/precip.mon.mean.nc

    Retrieval URL of the GPCP v2.3 file.

  5. usesdoi:10.1029/2007JD008470

    GHCN-CAMS land temperature (Fan and van den Dool 2008), used only for cell covariates.

  6. useshttps://downloads.psl.noaa.gov/Datasets/ghcncams/air.mon.mean.nc

    Retrieval URL of the GHCN-CAMS file.

  7. doi:10.5194/essd-11-1153-2019

    GRACE-REC: precipitation-driven linear storage model that is the basis of our symmetric model.

  8. doi:10.5194/hess-30-3221-2026

    Four-parameter linear recursive reconstruction of global storage; related linear-model approach.

  9. doi:10.5194/hess-25-511-2021

    Drought recovery time estimated from GRACE deficits and precipitation scenarios.

  10. CSR estimates show 96% recovery of California's July-September 2019-2022 water-storage loss in 2023 and 38% in 2025 sci:sha256:fd47a1b2b27bb4ce6df6e323179b5654419a5adc58201c473fdfb3e60417d2d2

    Campaign result on California storage recovery with the same CSR product; we test the recovery question globally.

  11. Runoff in 555 U.S. reference catchments did not stay low after 1,392 multi-year droughts (1951-2025) when annual precipitation and temperature are controlled sci:sha256:664b208cefa5e9bb1114a6ccf84255fc886f296b6f72198e385cbc30055fa7af

    Campaign result on US catchment runoff after multi-year drought; a related test of drought legacy in a different variable.

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